基于Mo-RVIKOR的混合多属性决策方法

针对复杂性和不确定性多属性决策问题,考虑定量和定性融合的属性形式,提出了模块化随机多准则妥协解排序法（Modular Random VlseKriterijumska Opti-mizacija I Kompromisno Resenje,Mo-RVIKOR）,该方法无需将信息统一,就能处理多种信息形式存在的多属性决策问题。采用精确数、随机变量处理定量评价信息,用概率语义术语集处理定性评价信息;通过改进离差最大化法确定属性权重;根据Mo-RVIKOR对决策对象进行排序;最后以某公司C2B定制化服务质量评测项目为例,验证了所提方法的有效性。     

First‐Price Auctions With General Information Structures: Implications for Bidding and Revenue

We explore the impact of private information in sealed‐bid first‐price auctions. For a given symmetric and arbitrarily correlated prior distribution over values, we characterize the lowest winning‐bid distribution that can arise across all information structures and equilibria. The information and equilibrium attaining this minimum leave bidders indifferent between their equilibrium bids and all higher bids. Our results provide lower bounds for bids and revenue with asymmetric distributions over values. We also report further characterizations of revenue and bidder surplus including upper bounds on revenue. Our work has implications for the identification of value distributions from data on winning bids and for the informationally robust comparison of alternative auction mechanisms.     

光滑暧昧模型下的不透明交易和管制措施研究

本文假定透明交易者对额外投资机会回报率的标准差(方差,投资风险)存在暧昧,这种认知暧昧性抑制了透明交易者的投资行为,会导致风险资产溢价过高及社会福利损失.透明交易者是暧昧厌恶的投资者,其投资决策依据光滑暧昧厌恶模型,需求函数呈现连续且光滑的特征.而不透明交易者,通过支付一定的信息获取成本获得私有信息而具有信息优势,他们是标准的风险厌恶的投资者.通过构建理性预期均衡,本文的研究发现:初始资产严格为正的透明交易者将获得严格为正的超额收益;提高信息获取成本将减少不透明交易者的比例,从而增加风险资产溢价,降低福利水平,因而不是一项好的管制措施;而旨在提高市场透明度降低交易者暧昧性的举措总有利于提高福利水平.     

房价波动、 收入水平对住房消费的影响——基于SYS-GMM估计方法的区域差异分析

基于生命周期-持久收入假说,在一般随机Ramsey模型的基础上,推导包含房价、收入和财富的住房消费函数,利用2002年至2013年31个省直辖市的面板数据,采用两步System-GMM估计方法考察我国房价波动和居民收入水平对住房消费的影响.实证结果表明:房价波动对全国居民住房消费具有显著的抑制作用;其中,滞后期和当期房价波动与当期住房消费负相关,挤出效应明显;未来一期房价波动与住房消费变化方向一致,存在积极的财富效应;此外,房价波动对东中西部各地区居民住房消费的抑制作用存在较大差异,西部地区抑制效应最为明显;滞后期住房消费与当期住房消费变动方向一致,人均可支配收入波动和人均年底储蓄余额对我国人均住房消费都起着重要的支撑作用.     

R2的复活——股价同步性研究评述与展望

R2是最近十几年迅速发展的一个研究课题,其研究取向从纯粹的计量经济学符号演变为股价同步性特征变量,并与公司特质信息含量联系起来,赋予了全新的内涵.学者们通过跨学科的交叉与融合,从法与金融理论、委托代理理论、信息不对称理论、公司治理理论等视角对R2背后的生成机制、作用渠道和影响后果展开富有成效的研究.本文首先梳理从资产定价模型到R2,再从R2到股价同步性中间的学理关系和因果顺承,接着回顾了关于R2形成机理与经济后果的相关讨论,然后对R2的学术争论进行总结和评述,最后就R2的溯源问题、以及文化与政治潜在影响对未来R2研究提出展望.     

社交网络、投资者关注与股价同步性

随着以微博、微信为代表的社交网络信息平台在中国的崛起,形成了新媒体时代下信息资讯生成与扩散的完整传播链条,深刻地影响着金融市场参与主体的学习认知习惯、投资决策理念、交易行为模式,最终影响不同金融资产的价格波动规律． 本文在新媒体时代情景下,以社交网络信息披露与传播平台为切入点,基于信息关注度、信赖度、更新频率等三层维度,构建社交网络微博信息质量指标体系,研究社交网络信息质量与股价同步性的内在关联关系． 研究表明: 微博信息质量与股价同步性有着显著的高度负向线性关联性,并且呈现出非线性 U 型关系． 即随着社交网络信息质量水平的提升,股价同步性逐渐降低到达最小值,而后又逐渐提高． 研究结论为证明上市公司社交网络微博平台对股价同步性有较强影响力,提供了中国金融市场的证据．     

启动农村消费的障碍及消除障碍的路径选择研究

消费是拉动内需,推动经济持续、健康发展的不懈动力,然而现阶段我国居民消费对GDP增长的促进作用较弱,尤其是农村消费,但由于受收入、物价、市场发达程度等因素的制约,农村消费长期以来一直被压制.采用定量、定性相结合的分析方法,通过构造数量模型分析影响消费的主要因素及影响程度,在此基础上重点对影响农村消费增长的原因进行分析,并提出相应的解决措施.     

A varying coefficient approach to estimating hedonic housing price functions and their quantiles

The varying coefficient (VC) model introduced by Hastie and Tibshirani [26 T. Hastie and R. Tibshirani, Varying-coefficient models, J. R. Statist. Soc. (Ser. B) 55 (1993), pp. 757–796.[Web of Science ®] , [Google Scholar]] is arguably one of the most remarkable recent developments in nonparametric regression theory. The VC model is an extension of the ordinary regression model where the coefficients are allowed to vary as smooth functions of an effect modifier possibly different from the regressors. The VC model reduces the modelling bias with its unique structure while also avoiding the ‘curse of dimensionality’ problem. While the VC model has been applied widely in a variety of disciplines, its application in economics has been minimal. The central goal of this paper is to apply VC modelling to the estimation of a hedonic house price function using data from Hong Kong, one of the world's most buoyant real estate markets. We demonstrate the advantages of the VC approach over traditional parametric and semi-parametric regressions in the face of a large number of regressors. We further combine VC modelling with quantile regression to examine the heterogeneity of the marginal effects of attributes across the distribution of housing prices.     

Combined asymmetric spatial weights matrix with application to housing prices

In this study, a combined asymmetric spatial weights matrix is proposed for capturing the unequal spatial dependence of housing prices, where the advantage of this matrix was demonstrated by a non-nested hypothesis test. To explore the heterogeneous spatial impacts of urban essential characteristics on housing prices over the eastern, central, and western regions of China, after the Lagrange multiplier and likelihood ratio tests, the spatial Durbin model using the proposed weights matrix was applied to each region. The estimation results showed that the direct impacts of college and new employment were significantly negative in the eastern region, but not significant in the central and western regions. By contrast, the direct impacts of hospitals and scenic spots were significantly positive in eastern China, but not significant in central and western China. In addition, the indirect impacts of the four variables were not significant in the three regions. These results suggest that in eastern China, the government may increase the requirements for using medical resources and close tourist attractions in a single city to cool down the skyrocketing housing prices in this area.